Overview AC/CA IP PRS VA Advisor

Prerequisite knowledge: basics about Image Processing, C/C++, OpenCV.

Laboratories

The OpenCV Application framework / Aplicatia cadru: Visual C++ 2013

Introduction to the OpenCV framework: OpenCV - introduction

Introducere in OpenCV : OpenCV - introducere

L1. Least Mean Squares Line Fitting / Potrivirea dreptelor folosind metoda celor mai mici patrate . support: Input data

L2. RANSAC - fitting a line to a set of points / Potrivirea dreptelor folosind metoda RANSAC . support: Input data

L3. Hough Transform for line detection / Transformata Hough pentru detectia dreptelor. support: images_Hough.zip

L4. Distance Transform (DT). Pattern Matching using DT / Transformata distanta DT. Potrivire de forme cu DT. support: prs_res_DT.zip.

L5. Statistical Data Analysis / Analiza Statistica a Datelor. support: prs_res_Statistics.zip.

L6. K-means Clustering / Grupare cu K-means . support: prs_res_Kmeans.zip.

L7. Principal Component Analysis / Analiza Componentelor Principale . support: PCA data.zip

L8. K-Nearest Neighbor Classifier / Clasificator bazat pe cei mai apropiati K vecini . support: KNN data.zip

L9. Naive Bayes Classifier / Clasificator Naive Bayes . support: Bayes data.zip

L10. Perceptron Linear Classifier / Clasificator linear Perceptron . support: Perceptron data.zip

L11. AdaBoost classifier / Clasificatorul AdaBoost. support: Adaboost data.zip

Project

Please send me an email with your Image Processing project title, at latest by Oct. 15.

Presence and evaluation

PRS, Presence and evaluation